Autonomous Robot Navigation with Sensor-Based Sub-Route Planning
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Solution Overview
Problem
Autonomous mobile robots face challenges in navigating through environments with obstacles due to discrepancies between their perceived location and actual location, leading to incorrect interpretation of obstacles and increased computational effort in establishing new sub routes.
Innovation Solution
The method involves providing an area map with initial route implications, sensing obstacles using a sensory system, reducing initial route implications by ignoring some mapped elements, and establishing a sensor-based sub route based on reduced route implications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot accounts for both mapped elements and sensed obstacles when establishing a sub route, then collision avoidance is improved, but computational effort increases and sub routes may become suboptimal
Solution Approach 1:
The patent extracts and removes mapped elements from the route planning consideration when a sensed obstacle is detected. The controller identifies that the sensed obstacle corresponds to a mapped element, then excludes the mapped element from sub route calculations, considering only the sensed obstacle. This extraction principle reduces computational complexity while maintaining collision avoidance by focusing planning efforts on the actual sensed obstacle rather than redundant mapped elements.
Solution Approach 2:
Instead of adding more constraints (both mapped elements and sensed obstacles) to the route planning problem, the patent inverts the approach by removing constraints. When a sensed obstacle corresponds to a mapped element, the mapped element's route implications are reduced or ignored, effectively subtracting constraints from the planning problem. This inversion reduces computational burden while preserving safety through the sensed obstacle data.
2Adaptability or versatility
If the robot uses SLAM or MCL for positioning in indoor environments, then navigation capability is improved, but location accuracy deteriorates due to discrepancies between perceived and actual location
Solution Approach 1:
The patent employs feedback by continuously comparing sensed obstacles with mapped elements during navigation. When the robot detects a sensed obstacle that corresponds to a known mapped element, this feedback loop triggers the controller to reduce the mapped element's route implications. This feedback mechanism compensates for SLAM/MCL location inaccuracies by using real-time sensor data to adjust route planning, effectively correcting for perceived location discrepancies without requiring perfect positioning accuracy.
3Reliability
If the robot establishes sub routes considering all mapped elements, then route planning completeness is improved, but navigation speed deteriorates due to increased computational requirements
Solution Approach 1:
The patent extracts irrelevant mapped elements from the route planning process by identifying when sensed obstacles correspond to mapped elements. The controller removes these mapped elements from consideration, reducing the number of constraints that must be evaluated during sub route establishment. This extraction maintains route planning completeness for actual obstacles while improving navigation speed by eliminating redundant computational overhead from inaccurate mapped element representations.
Data Source
AI summary
The invention relates to a method for dynamically navigating an autonomous mobile robot. The method comprises the steps of: providing an area map relating to mapped elements having initial route implications; providing a planned robot route through said area map, wherein said planned robot route is based on circumnavigating at least some of said mapped elements according to said initial route implications; maneuvering said autonomous mobile robot through said planned robot route at least partly based on sensing robot surroundings of said autonomous robot using a sensory system of said autonomous mobile robot; sensing one or more sensed obstacles in said robot surroundings using said sensory system, wherein said one or more sensed obstacles differentiate from said mapped elements; reducing said initial route implications of at least some of said mapped elements to establish reduced route implications; and establishing a sensor-based sub route based on said reduced route implications.